2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)最新文献

{"title":"Application of SAR images in Iceberg Classification by using ConvNet-2","authors":"Valaparla Rohini, Pamidi Rama Tejaswini, Sappa Visweswara Rao, Shaik Aseef, Vallabhu Kathyayani Karishma","doi":"10.1109/ACCAI58221.2023.10200690","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10200690","url":null,"abstract":"Iceberg areas are not safe for transportation because based on climate changes icebergs are melting and not showing a dangerous way in sea areas. Based on the vision we can’t identify all the icebergs in the ocean area. So, by using a Deep learning algorithm we can classify icebergs through satellite images. In the past decades, several machine learning algorithms are implemented for classification of the images. But our aim is to implement an application to classify the iceberg by using synthetic-aperture radar (SAR) images which are available at the Kaggle repository. The Data set was from the Statoil C-CORE East Coast of Canada. Here we classify the icebergs by using remotely sensed data. For this data, the Convolutional Neural Network is used for image classification and extraction of the features of images deeply. The CNN algorithm was implemented on the SAR images and achieved 99.8% training and 89.5% of validation accuracy with high time consumption when training the dataset.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114504321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Waning Immunity Index Model using Spiking Neural Networks for COVID-19 Pandemic in the geographic context of India","authors":"S. S, R. P, S. S","doi":"10.1109/ACCAI58221.2023.10201080","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10201080","url":null,"abstract":"Spiking Neural Networks (SNN) are biologically inspired networks working on the principle of communication triggered while crossing of threshold potentials. During the COVID-19 pandemic, immunity has been acquired by the population in a geographical location by infections and immunizations. The Waning Immunity Model (WII) has been used to apply the method of SNNs so that the results of the model provide a better way of understanding its effects. The dataset considered in this research is for a time period of six months during the years of 2021 and 2022 focusing on the geographical location of India. Based on the proposed new model, the spike in the WII index is clearly evident in the first half of the time period under consideration, This model will help the healthcare and governments officials to plan for the booster doses to be administered to the human population for reinvigorating the antibodies effectively fighting the COVID-19 virus.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115122404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, Analysis and Implementation of Microstrip UWB Antenna to monitor the Fetus in Uterus","authors":"J.J. Lakshaya, Kaviyadharshini. N, K. S., I. Sheeba","doi":"10.1109/ACCAI58221.2023.10199904","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10199904","url":null,"abstract":"With the growth of the healthcare and biomedical industries, biomedical telemetry antenna has attracted a lot of interest. With the help of conventional hospital visits and follow-up routine check-ups, it is now possible to remotely monitor a patient's physiological indications. This is made possible by the Use of integrated Hilbert curve expandable antenna technology. The integrated Hilbert curve expandable biomedical antenna devices (IHEBAD) that have been proposed play a significant part in the monitoring of the fetus found in the patient using wireless telemetry such as an ISM (2.45 GHz) and UWB (4.25 GHz) band. For the extendable antenna, a number of elements need to be taken into account, including miniaturization, patient safety, biocompatibility, low power consumption, reduced frequency band of operation, and dual band specifications. Choosing an antenna is a difficult task for Hilbert to design. This paper presents the key finding in the integrated Hilbert curve expandable biomedical antenna proposal with wearable substrate. To confirm the use of the suggested antenna design, the proposed antenna's essential characteristics are analyzed. They also demonstrate a good level of simulation agreement.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123477077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Efficient Routing Algorithm with Mobile Sink Assistance in Wireless Sensor Networks","authors":"S. Sugumaran, C. Geetha, S. S., P. C. Bharath Kumar, T. D. Subha, J. Arunkumar","doi":"10.1109/ACCAI58221.2023.10201142","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10201142","url":null,"abstract":"In recent years, WSNs have been a hot topic. To simplify, imagine a network of several sensors that are autonomously structured and work together to gather, process, and communicate data about targets to a far-off control room. As the sensor nodes in a WSN are in charge of relaying data from the source to the destination, it is crucial that this process be carried out in an energy-efficient manner in order to keep the network operational. The installation of a mobile sink node, which may move along predetermined paths, can successfully mitigate this issue by causing hot spot nodes to be more uniformly distributed. In this study, we provide a routing scheme that minimizes energy consumption by using clustering and washbasin mobility. We cluster the entire network and investigate how many mobile sinks have an effect on the longevity of the network. Our simulation findings reveal that the optimal number of mobile sinks, in terms of network performance, is around 4.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122013701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic Monitoring and Controlling of Wi-Fi Based Robotic Car","authors":"Shreya Singh, M. Dilshad, M. Pushpavalli, P. Abirami, M. Kavitha, R. Harikrishnan","doi":"10.1109/ACCAI58221.2023.10199457","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10199457","url":null,"abstract":"This project aims to design and implement a wifi based robotic car that can be monitored and controlled remotely using an Arduino NodeMCU, a camera, and various sensors. The car is equipped with a microcontroller (Arduino NodeMCU) that acts as the main control unit, a wifi module that provides connectivity to a remote device/computer, a camera for real-time image capture and analysis, and various sensors (such as ultrasonic, IR, etc.) for obstacle detection and avoidance. The remote device/computer can send commands to the car to control its movement and receive real-time data such as sensor readings, camera feed, etc. The project will demonstrate the capabilities of the combination of hardware and software components to create a fully functional, autonomous wifi based robotic car.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126180282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical Assessment and Detection of Suicide Related Posts in Twitter using Artificial Intelligence enabled Classification Logic","authors":"T. Ravishankar, Ata Kishore Kumar, J. Venkatesh, M.Ramkumar Prabhu, V. S. Bhargavi, MuthamilSelvan.S","doi":"10.1109/ACCAI58221.2023.10201110","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10201110","url":null,"abstract":"The identification of suicidal thoughts in online social networks is an expanding field of study fraught with major challenges. Recent studies have shown that the readily available data, dispersed over many online life phases, contains useful clues for accurately identifying persons with suicidal intentions. The primary challenge in preventing suicide is learning to recognize and respond appropriately to the sometimes-confusing risk factors and warning indications that may precipitate an attempt. Indicators useful for diagnosing people with suicide thoughts can be found in publicly available material shared over social media platforms, according to recent studies. Understanding and recognizing the myriad risk factors and warning symptoms that may precede a suicide attempt is the primary difficulty in this area of public health. In this research, we developed a benchmark for multi-class categorization using machine learning models. We used a majority classifier, a frequency-based technique, and two deep learning models as our models. Both deep learning models outperformed the majority and the word frequency classifier, with results that were very comparable. These classification results are on par with the state-of-the-art on similar problems and, in most cases, with human results.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128512847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A New Proposed Modified Shortest Path Algorithm’s Using Dijkstra’s","authors":"Pallab Banerjee, Pappu Kumar, B. Kumar, Kanika Thakur","doi":"10.1109/ACCAI58221.2023.10199281","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10199281","url":null,"abstract":"Roads are essential for the daily mobility of residents in various locations to work, education, and other destinations as well as for the transportation of their commodities. Roads continue to be one of the most popular modes of travel and transportation even in today's society. determining the shortest route between two places appears to be a significant issue with the road networks. To address the, a variety of applications were introduced by creating a number of shortest path algorithms. Finding the shortest route still presents a challenge. road systems. This work proposes a novel algorithm, the Modified Dijkstra's Shortest Path (MDSP) algorithm, which uses many parameters to solve the shortest path issue. To demonstrate the effectiveness of the suggested algorithm, it is compared to the current algorithm.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127201965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chatbot for Trading Cryptocurrency","authors":"K. Jaspin, Sanjeev S, S. S","doi":"10.1109/ACCAI58221.2023.10200405","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10200405","url":null,"abstract":"Many chatbots have been created, offering a variety of services via various channels. A brand-new conversational agent in the quickly evolving realm of technology is a chatbot. Chatbots are getting more and more common because of their intelligence and machine learning. A chatbot is an extension of human interaction technologies like phone calls and social media. Similar to digital or virtual currency, cryptocurrency is a fresh extension created to function as a means of exchange. Investors and other interested parties are keen to learn more about this new form of currency's capabilities in the current world of digital exchange. A chatbot is one method that might be used to swiftly and automatically retrieve information. A chatbot assists the users by providing services to themselves, and they always favour text-based support. Cryptocurrency is a decentralized, blockchain-based, encrypted form of digital money. Blockchain refers to a digital ledger that is accessible only to authorized users in the context of cryptocurrencies. This ledger records transactions involving a range of resources, including money, property, and even intangible assets. The chatbot is deployed for the purpose that it serves the customers at any time. Humans can work only for a limited time whereas, the chatbot is available 24x7 for customer support and assistance. The chatbot helps users in trading cryptocurrencies without any human involvement. It can handle all the queries related to cryptocurrencies that are raised by the customer. And the chatbot can also converse in multiple languages. This helps a lot of customers to use the chatbot in an easy and effective manner. Customers feel so easy to work with the chatbot that it responds to them in the language that they choose to converse. The chatbot stores all the information related to the customer like details of the customer, time stayed on the chatbot, the way customer interacts with the chatbot, etc. The chatbot can predict how likely the user of the chatbot can become a customer to the company of the chatbot. The agents of the company can view the live visitors using the chatbot and their conversation that they have with the chatbot.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129955531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proxy-Based Re-Encryption Design for the IoT Ecosystem","authors":"Kandula Srikanth, Pathuri Guna Rajesh, Nallapaneni Durga Prasad, Mohammed Asmathulla, Thallapureddy Praveen Kumar Reddy","doi":"10.1109/ACCAI58221.2023.10200337","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10200337","url":null,"abstract":"Protect data in transit with a proxy-based re-encryption solution designed specifically for the Internet of Things ecosystem's needs. Because of identity-based encryption and proxy re-encryption can safely outsource to the cloud with proxy-based re-encryption technology. To compensate for the limitations of IoT devices, it delegated complex task processing to a proxy device located closer to the network's edge. Furthermore, distributing cached material through the proxy using information-centric networking features, improves service quality and network capacity utilization. The proposed research and security strategy review demonstrate that our method protects data in every sense, from granular control over who can access what to the elimination of key system bottlenecks.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129021135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep convolutional neural networks and transfer learning for classifying malignant and benign skin cancer","authors":"G. B, Thiagarajan R, Bhavitha D, Dharshini R, Madhunisha T R","doi":"10.1109/ACCAI58221.2023.10199438","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10199438","url":null,"abstract":"Over 123,000 occurrences of skin cancer cases are identified globally each year. The ability to identify malignant skin lesions as early as possible would be a huge benefit to clinicians from reliable automatic skin cancer screening systems. In the last five years, it appears that methods based on deep learning perform better than conventional methods for classifying images. Techniques based on machine learning are less practical because they need thousands of labelled images for each class to be trained. We propose a precise method to distinguish benign from malignant skin lesions using deep convolutional neural networks with transfer learning (DCNNT). The first step in our process is to eliminate noise and artefacts from the input images. In the second step, the input images must be normalized and features needed for classification extracted. The third is to augment the data with additional images, which improves classification accuracy. We employ transfer learning models, such as Densenet121, MobileNet, ResNet50, and VGG19 to assess the performance of our suggested DCNNT model. On a dataset comparing benign and malignant tumours, we obtained the highest training and testing accuracy with DCNN and DenseNet transfer learning model, with 98.16% training and 92.42% testing. Our DCNNT model is dependable and robust. We discovered that our suggested model performed better than other model.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130753178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}